Top 9 Benefits Of Data Cleansing That Will Blow Your Mind

All around the globe, there is one holiday season where all of us are sent on a mission.

Mission to clean our houses and give away unnecessary stuff.

Your business data is no different. It needs regular cleaning.

Did you know that data decays at an average rate of 2 percent per month, which means 25 to 30 percent of your organization’s contact data to go bad each year?

Considering most marketing activities have gone digital, data has taken a significant place.

In fact, 63% of marketers report spending more on data-driven marketing and advertising last year, and 53% said that “a demand to deliver more relevant communications/be more ‘customer-centric’” is among the most important factors driving their investment in data-driven marketing”.

But, why is data cleansing required? What are the benefits of data cleansing

Data-driven marketing allows you to

Respond to change in customer dynamics and preferences

Analyse the shift in buyer’s behavior

Nurture leads effectively etc.

For all this to happen, cleansing data is important. If your data is inaccurate, your decisions will not have the desired impact leaving you and your boss frustrated.

If your teams are already overwhelmed with the existing workload, you can always outsource it to an agency.

1. Knowledge of customer base

Importance of data cleansing in researching your customers cannot be ignored! If you have the correct data on your customers, it is pure gold.

It can be used to understand buyers persona, behavior, preferences and sales journey. This information can help you craft accurate buyer personas and nurture leads strategically.

Also, personalized communication becomes super easy!

85% of organizations have seen improvements in timely and personalized customer communications by improving data quality.

2. Easy to segment campaigns

If you have the required data, it is easy to segment your audience. For example, if your product can be used by both mid sized as well as big sized companies, you will want to segment campaigns. Benefits of data cleansing like scalability may be attractive to big companies but utility and affordability are important for mid sized businesses.

Segmenting your audiences can result in tailored content which talks directly to them and solves their problems.

The more targeted your messages are, the likeliness of an individual to engage, support and buy increases by leaps and bounds.

3. Better customer relationships

You are a big company with multiple products which are utilized by different types of companies.

Would you send them “one message fits all” content?

Obviously, no. You will need to tailor content to all segments.

If you send relevant data to your audience, they are most likely to engage with you and spread the good word. Irrelevant offers and content often annoys people, waste their time, get tossed away into the bin, spoils relationships and reputation.

Using information to segment, target and tailor methods to suit a specific audience will increase your ROI and improve customer relationships.

4. Reduces data duplication and redundancy

If your data is clean, you can avoid duplication of efforts (for example, sending the same email twice. One to Mr. John and another to John.) and redundancies that can cost you time, money and reputation.

5. Rescues from inaccurate marketing

Outdated data will always lead you to choose incorrect form of marketing.

Imagine relying on 5 year old database. It may still say that your target audience is driven by newspaper ads. But, what if, your target audience started preferring the digital space?

While you advertise in the newspapers and get a few leads, what actually happened?

You missed out on leads, opportunity to double revenue and the biggest of all – You have no idea who your audience is and what they prefer!

6. Increases ROI on email marketing

Data cleansing and scrubbing are damn important for any email marketing campaign. If your data is old, you will have lots of unopened and bounced emails.

Has it ever happened to you that you set up a campaign and very few opened it? You tried and tried but no tactic seems to be working?

Because a significant percentage of email addresses inevitably become bad over time (from 20% to 30% on average)

One of the benefits of data cleansing and scrubbing is that it keeps email list hygiene and maximize ROI (in the form of revenue, click through rates, qualified leads, open rates etc) from email marketing campaigns.

7. Accuracy in reporting and further strategizing

As a marketer, your biggest challenge is to justify marketing budget.

You can run as many reports on bad data but you will always get a fragmented picture of what is working and what is not. Not only do you run the risk of reporting inaccurately, but you will end up spending the marketing budget on wrong channels.

What happens in the process?

Stress. Loss of money. ZERO ROI. Lower than optimum revenue. Should I continue?

8. Make best use of talent

If you are working on bad data, the effort of all the relevant teams is in vain.

Having clean and accurate database will help your business to ensure that the employees are making best use of their talent and working hours. It will also prevent them from contacting customers with outdated information or sending new product/services information to unused contact details.

Remember, every call unanswered or every bounced email has an attached cost.

You can avoid this by maintaining clean data.

9. Reduce unnecessary costs

If you outsource data cleansing and scrubbing like the rest of the 41%, you can reduce further costs. You will get access to latest tools (without having to pay for the license), experienced staff (without being on payroll) and the much required expertise (without paying extra).

There you go. From increased customer satisfaction and better relationships to increasing profitability through targeting and tailoring; there are numerous benefits of data cleansing and maintaining good quality data.

Each and every business owner or marketing manager should ensure that the data is clean by implementing a process and a data quality routine.

Author Kartik Jha

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